Metabolomics

CSAMA 2019

Content

(Brief) introduction to metabolomics
Preprocessing of LC-MS data
Normalization
Annotation/identification

Metabolite? Metabolism?

Glycolysis

Key metabolic pathways common to all cells.
Creates energy by converting glucose to pyruvate.

Metabolite? Metabolism?

Glycolysis

Metabolite? Metabolism?

Glycolysis

Metabolite? Metabolism?

Glycolysis

Metabolite? Metabolism?

Glycolysis

Metabolite? Metabolism?

Glycolysis

Metabolite? Metabolism?

Glycolysis

Metabolites: intermediates and products of cellular processes.

Metabolomics?

Large-scale study of small molecules (metabolites) in a system (cell, tissue, organism).

Comparison of the different -omes:

Genome: what can happen.

Transcriptome: what appears to be happening.

Proteome: what makes it happen.

Metabolome: what actually happened.

Metabolome influenced by genetic and environmental factors.

How can we measure metabolites?

Nuclear Magnetic Resonance (NMR) - not covered here.
Mass spectrometry (MS)-based metabolomics.

Metabolites small enough to be directly measured.
Most metabolites uncharged - need to create ions first.

Mass Spectrometry (MS)

Problem: unable to distinguish between metabolites with the same/similar mass-to-charge ratio (m/z).
Solution: additional separation of metabolites prior to MS.

Liquid chromatography

Sample is dissolved in a fluid (mobile phase).

Liquid chromatography

Sample is dissolved in a fluid (mobile phase).
Mobile phase carries analytes through column (stationary phase).

Liquid chromatography

Sample is dissolved in a fluid (mobile phase).
Mobile phase carries analytes through column (stationary phase).
Separation based on affinity for the column’s stationary phase.

Liquid chromatography

Sample is dissolved in a fluid (mobile phase).
Mobile phase carries analytes through column (stationary phase).
Separation based on affinity for the column’s stationary phase.
HILIC (hyrophilic liquid interaction chromatography):
- Hydrophilic, polar stationary phase.
- Analytes solved in mobile phase.
- Analytes separated by polarity: compounds with low polarity elute first, with high polarity later.

Liquid Chromatography Mass Spectrometry (LC-MS)

LC-MS data has 3 dimensions:

m/z, retention time, intensity.

Analyze data along rt.

LC-MS data preprocessing

Chromatographic peak detection
Alignment
Correspondence

Chromatographic peak detection

Aim: identify chromatographic peaks in the data.

Chromatographic peak detection

Aim: identify chromatographic peaks in the data.

Chromatographic peak detection

centWave [Tautenhahn et al. BMC Bioinformatics, 2008]:

Step 1: identify regions of interest.

Chromatographic peak detection

Step 2: peak detection using continuous wavelet transform.
Allows detection of peaks with different rt widths.

Chromatographic peak detection

MSnbase: data import with readMSData.
xcms: peak detection with findChromPeaks and algorithm-specific parameter object.

cwp <- CentWaveParam(peakwidth = c(2, 10), snthresh = 5)
data <- findChromPeaks(data, param = cwp)
head(chromPeaks(data), n = 3)

##             mz    mzmin    mzmax     rt rtmin  rtmax     into     intb
## CP001 114.0907 114.0899 114.0929  1.954 0.280  3.907 1559.829 1555.923
## CP002 114.0913 114.0884 114.0929  5.860 4.465  8.650 1890.221 1885.757
## CP003 114.0914 114.0899 114.0929 10.882 8.650 13.114 1950.953 1946.210
##           maxo  sn sample
## CP001 584.9510 584      1
## CP002 601.8881 601      1
## CP003 691.9580 691      1

Alignment

Aim: adjust differences in retention times between samples.

Same analyte elutes at slightly different time between measurements.

Why? Age of column, temperature …

Alignment

Many algorithms available [Smith et al. Brief Bioinformatics 2013]

xcms: adjustRtime function with PeakDensityParam [Smith et al. Anal. chem. 2006] or ObiwarpParam [Prince et al. Anal. chem. 2006].

Correspondence

Aim: group peaks representing same ion species across samples.
Result: matrix of abundances, rows features, columns samples.

Correspondence

Aim: group peaks representing same ion species across samples.
Result: matrix of abundances, rows features, columns samples.

Correspondence

Aim: group peaks representing same ion species across samples.
Result: matrix of abundances, rows features, columns samples.

Correspondence

xcms: groupChromPeaks with NearestPeaksParam [Katajamaa et al. Bioinformatics 2006] and PeakDensityParam [Smith et al. Anal. chem. 2006].

peak density approach (for a given m/z slice):

Correspondence

xcms: groupChromPeaks with NearestPeaksParam [Katajamaa et al. Bioinformatics 2006] and PeakDensityParam [Smith et al. Anal. chem. 2006].
peak density approach (for a given m/z slice):

Preprocessing result

Numeric matrix with abundances.
Normalization.
Identification of features of interest.
Annotation.

Normalization

Sample-specific effects.
Effects related to batch/measurement run.
LC-dependent effects: seem to affect each metabolite in a different way.

Normalization

Good practice:
- QC samples measured repeatedly.
- Internal standards.
- Replicates.
- Measurement of study samples in randomized order.

Popular normalization methods:
- RUV [De Livera et al. Anal. Chem. 2015]
- linear models [Wehrens et al. Metabolomics 2016]
- linear and higher order models [Brunius et al. Metabolomics 2016].

Annotation/Identification

Feature != metabolite.

## DataFrame with 4 rows and 4 columns
##                  mzmed            rtmed           POOL_1           POOL_2
##              <numeric>        <numeric>        <numeric>        <numeric>
## FT001 105.041814839707  167.96077773118 229.490739260736 3093.75184315684
## FT002 105.041653033614 157.082078655729 4762.39872227773 6601.45091358641
## FT003 105.069636149683 31.8109676438667 699.723986763237 1033.23232267732
## FT004  105.11027064078 63.7514649484463 20211.2633706294 15839.5504368189

Feature characterized by m/z and retention time.

Annotation based on m/z matching

Match mass against database.
- The Human Metabolome Database (HMDB): https://hmdb.ca
- Chemical Entities of Biological Interest: https://www.ebi.ac.uk/chebi
- PubChem https://pubchem.ncbi.nlm.nih.gov
- …
Will result in many hits.

m/z is not the mass.

Mass of an [M+H]+ ion: m/z - mass of 1 hydrogen.

Different ions from the same compound: [M+H]+, [M+Na]+, …

Improved Annotation

Annotate features based on m/z and:

retention time: requires measurement of compound/standard on the same LC-MS setup.

MS2 spectrum:
- Requires LC-MS/MS data (DDA or DIA).
- Reference spectrum has to be available in database.
- GNPS: spectral similarity network: group spectra/compounds into classes.

Afternoon metabolomics lab

LC-MS data handling (MSnbase).
LC-MS data preprocessing using xcms.